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公开(公告)号：US11886455B1
公开(公告)日：2024-01-30
申请号：US18146256
申请日：2022-12-23
申请人： Splunk Inc.
IPC分类号： G06F16/248 , G06F16/951
CPC分类号： G06F16/248 , G06F16/951
摘要： Systems and methods ingest machine data including logs, metadata, and cost and usage information from multiple heterogeneous cloud services. The machine data is saved as events. An application retrieves the metadata, events, metrics, and logs and causes an easy to understand visual representation of costs, resource usage, and non-compliance for each of a client's cloud services. Further, the data across the client's multiple heterogeneous cloud services is normalized to provide visual representations that compare the costs, resource usage, and non-compliance across the client's multiple heterogeneous cloud services. Further, machine learning aspects of the application can provide recommendations and trend analysis for cloud service asset usage.
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公开(公告)号：US11768836B2
公开(公告)日：2023-09-26
申请号：US16582205
申请日：2019-09-25
申请人： Splunk Inc.
IPC分类号： G06F15/16 , G06F16/2457 , G06Q10/00
CPC分类号： G06F16/24573 , G06Q10/00
摘要： A service monitoring system (SMS) produces key performance indicator (KPI) scores that indicate the performance of a service. To produce the KPI scores, the SMS may process the data for a large number of machine entities that perform the service. This data can be processed on a per-entity basis to produce a per-entity KPI score representing the contribution of a particular machine to the overall KPI. The per-entity KPI scores can be transformed to statistical representations which can be visualized as a distribution stream graph. The visualization may be presented with interactive aspects. Automatic entity definitions may also be generated based on content derived from the processed data.
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公开(公告)号：US11537627B1
公开(公告)日：2022-12-27
申请号：US16147181
申请日：2018-09-28
申请人： Splunk Inc.
IPC分类号： G06F16/248 , G06F16/951
摘要： Systems and methods ingest machine data including logs, metadata, and cost and usage information from multiple heterogeneous cloud services. The machine data is saved as events. An application retrieves the metadata, events, metrics, and logs and causes an easy to understand visual representation of costs, resource usage, and non-compliance for each of a client's cloud services. Further, the data across the client's multiple heterogeneous cloud services is normalized to provide visual representations that compare the costs, resource usage, and non-compliance across the client's multiple heterogeneous cloud services. Further, machine learning aspects of the application can provide recommendations and trend analysis for cloud service asset usage.
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公开(公告)号：US20200019555A1
公开(公告)日：2020-01-16
申请号：US16582205
申请日：2019-09-25
申请人： Splunk Inc.
IPC分类号： G06F16/2457
摘要： A service monitoring system (SMS) produces key performance indicator (KPI) scores that indicate the performance of a service. To produce the KPI scores, the SMS may process the data for a large number of machine entities that perform the service. This data can be processed on a per-entity basis to produce a per-entity KPI score representing the contribution of a particular machine to the overall KPI. The per-entity KPI scores can be transformed to statistical representations which can be visualized as a distribution stream graph. The visualization may be presented with interactive aspects. Automatic entity definitions may also be generated based on content derived from the processed data.
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公开(公告)号：US20160103883A1
公开(公告)日：2016-04-14
申请号：US14859243
申请日：2015-09-18
申请人： Splunk Inc.
IPC分类号： G06F17/30
摘要： Methods are disclosed to take advantage of the early collection of machine data from a new or changed entity in a computing environment in order to update the definitional information about entities used by a service monitoring system. In some embodiments, the process undertaken to recognize new or changed entities in an IT environment from collected machine data may be informed by the expertise of a particular subject matter area by installing that intelligence in a codified form packaged as a domain add-on to the service monitoring system.
摘要翻译： 公开了利用在计算环境中从新的或改变的实体早期收集机器数据的方法，以便更新关于由服务监视系统使用的实体的定义信息。 在一些实施例中，从收集的机器数据识别IT环境中的新的或改变的实体的过程可以由特定主题区域的专业知识通过将该智能安装在作为域附加的 服务监控系统。
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公开(公告)号：US10474680B2
公开(公告)日：2019-11-12
申请号：US14859243
申请日：2015-09-18
申请人： Splunk Inc.
IPC分类号： G06F17/30 , G06F16/2457 , G06Q10/00
摘要： Methods are disclosed to take advantage of the early collection of machine data from a new or changed entity in a computing environment in order to update the definitional information about entities used by a service monitoring system. In some embodiments, the process undertaken to recognize new or changed entities in an IT environment from collected machine data may be informed by the expertise of a particular subject matter area by installing that intelligence in a codified form packaged as a domain add-on to the service monitoring system.
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